Category: Telecom Insights & Analytics

  • Does a Digital Lifestyle offer Operators opportunities, or is the path more ominous?

    Does a Digital Lifestyle offer Operators opportunities, or is the path more ominous?

    It stands to reason that the Digital lifestyle of consumers will dramatically impact how operators generate revenues over the next 10-15 years. Transformations are taking place that will move activities, entertainment, commerce, healthcare, transportation, and most other aspects of our lives into Digital modalities. This has invited thousands of micro-providers of applications and networks into the mix, quickly marginalizing the value of the operator to merely an “enabling pipe.” This puts the operator into a competitive situation, ultimately impacting margins. But that’s only on the revenue side of the equation… the story could become far more complex.

    For an operator, the days of 25%-40% EBIDTA are waning, if not almost gone (in many regions). Pressures on pricing remain downward, with new product offers being the primary method to sustain acceptable revenues and margins. This has opened the door for some impressive creativity by many operators, especially in developing markets. In many cases no market appears off limits, as seen by the offerings by progressive organizations like MTN in Africa: Who would have anticipated an operator would offer personal transportation services rivaling Uber?

    These seemingly odd moves are, in fact, brilliant moves by operators to seek new sources of revenues as their businesses are being redefined by the digital services we are quickly becoming reliant on. The impacts on revenue models due to this change in the business are stunning: Traditional billed services like voice, and even data, are fading in importance. Revenue models are instead focusing more on casual services, pay-per-use services, marketplace services, etc. Put more simply, the “pipe” is no longer where the earning potential lies for the operator.

    So now a previously non-agile, large operator business is finding itself competing with, and in many cases partnering with, literally thousands of aggressive, hungry micro-entities that provide products and services accessed by the networks. There is less reliance on monthly guaranteed revenue; the battle for revenue very often resides in millions of micro-transactions.

    All of the discussion cannot focus entirely on revenues, however. Margins are also sustained by costs. Agility, therefore, must exist on the cost side of the operator business. In the old world of monthly recurring and predictable revenues, costs could be managed and allocated more confidently. Opex and Capex planning and forecasting practices were based on budgeting with a high degree of certainty. But as revenues models are changing, so must cost models. Where possible, operators will need to employ similar creativity to curbing costs, as they are with earning revenues.

    How can operators, therefore, modify cost models in the business to be as aggressive and variable as the revenue models they rely upon? This is where the opportunities for SDN/NFV networks can shave significant costs, while changing operator cost models in ways that were not previously achievable.

    Software-Defined Networks (SDN) and Network Function Virtualization (NFV) will allow operators to provide Network-on-Demand and Service-on-Demand models to consumers, while effectively minimizing, if not eliminating the need for human intervention. The costs associated with truck rolls, call centers, and expensive specialized network equipment will be dramatically reduced, resulting in decreased Opex and Capex burdens on the business. The savings need to expand further, however.

    In current cost models, operators must deploy and maintain network services around the clock, which consumes significant and ongoing expenses. However, if a network is based on SDN/NFV architectures, the deployed services are no longer in a fixed position in the network, simply because they are now software-defined and/or virtualized. This means an intelligent network can move assets where needed, and when needed. These assets are capitalized as licensed instances; so now an operator can have a pool of 1,000 licenses for a virtual service, and deploy them only as necessary.

    This type of dynamic deployment model should allow operators to negotiate dynamic cost models as well; imagine only paying for a license when you have it deployed (and it is generating revenue). While this idea may seem far-fetched, consider that now the network functions we are discussing are no longer controlled by a few network equipment and function providers; micro-entities (application developers) can now produce those functions, often at far less expensive price points.

    The business transformations taking place in operators globally are forcing entirely new ways of addressing margin pressures, as the revenue and cost variables operators have historically used are no longer the same. Looking beyond margins in consumer-facing products and services, new network cost models must be explored, especially since those models were based on what is now an outdated means to earn revenues.

  • Customer Analytics:  Data Breaches and Consumer Trust

    Customer Analytics: Data Breaches and Consumer Trust

    In this (possibly) final blog of this series I will be looking at how customers are becoming increasingly concerned at companies’ inability to keep their data safe, and how high publicity data breaches are eroding public confidence.

    I previously wrote how it was possible to know where someone stood on issues of internet security just by checking their birth date. Those born after 1980, the so called Generation Y, or Millennials, are generally more comfortable sharing information online.   But things are gradually changing. In a 2014 survey by eMarketer it was found that Generation Y and Z were also becoming significantly more concerned about how well companies protected their personal data.

    This concern can have a major impact on a company’s profits, as a recent report by the Ponemon Institute’s 2015 Cost of Data Breach Study (in conjunction with IBM) showed:-

    Lost business has, potentially, the most severe financial consequences for an organization. The cost increased from a total average cost of $1.33 million last year to $1.57 million in 2015. This cost component includes the abnormal turnover of customers, increased customer acquisition activities, reputation losses and diminished goodwill. The growing awareness of identity theft and consumers’ concerns about the security of their personal data following a breach has contributed to the increase in lost business

    By studying many data breaches across many industries, Ponemon have developed an approach whereby they can attach cost per record lost in order to estimate the cost of data breaches. What they have found is that, not only are data breaches becoming more common, but they are also becoming more costly.

    The average cost paid for each lost or stolen record containing sensitive and confidential information increased 6 percent, jumping from $145 in 2014 to $154 in 2015.

    2015 was perhaps the worst year so far for data breaches. NetworkWorld’s Top-10 data breaches of 2015 reported that many firms became the victim of very public data breaches including

    • Children’s toy companies (vTech)
    • Phone companies (T-Mobile, TalkTalk)
    • Healthcare firms (Premera, Anthem)
    • Dating agencies (Ashley Madison)
    • Government departments (IRS)
    • Security consultancies (Hacking Team)

    + Many more.

    The trend does not look good, with the number of breaches predicted to increase in both size and cost for the foreseeable future.

    Consumers are now realising that many companies are not vigilant enough in protecting their data, but just as bad, that customer data is being used in ways that are inappropriate and may adversely affect the consumer.

    In a poll conducted by leading consultancy Radius Global 78% of internet users said they only purchased from companies they trusted.

    The message is clear. If companies are to use customer’s data to provide a better service then they must do everything in their power to ensure the security of their systems and the responsible use of customer data, or run the risk of facing big fines and a catastrophic loss of consumer trust.

    Big data and advanced analytics are forcing governments to bring in new regulations to ensure that companies use customer data responsibly, but it’s in every companies interest to ensure that the bond of trust is not broken.

  • Customer Analytics:  Securing our Future

    Customer Analytics: Securing our Future

    In the previous blog in this series I looked at how the use of persona, and creating customer journey maps for those persona, can give new insights on how to engage customers. By collecting customer data and tracking user interactions across all touchpoints, it’s possible to not only create an revealing profile of a customer’s interests and behaviour, but also better understand if the products and marketing are addressing customer’s wants and needs.

    Technology is now rapidly opening up new sources of customer data including everything from health and well-being apps to our children’s activity online. Soon our heating systems, cars, refrigerators and every other connected appliance that’s about to hit the shelves will be churning out a stream of data back to the marketing departments of big corporations. The effective use of this big data undoubtedly has great potential to improve our lives, but there is also an increased risk that the individual’s privacy could be compromised, or the data could also be used to discriminate against an individual unfairly. In a recent case in the UK vulnerable customers were advised to buy energy on tariffs that were far higher than others available.   The same is true of insurance and medical care, and many cases exist where it’s been found that corporations are exploiting data to prey on the vulnerable. Add to this the substantial risks of identity theft and fraud as a consequence of data breaches, and consumers could be forgiven for feeling anxious about how well their data is being protected, and how it’s being used.

    In an effort to stop corporations from exploiting big data negatively and better protect consumers the European Union has raised the bar on data protection by drafting the the General Data Protection Regulation (GDPR). This new set of rules will apply not only to countries within the EU, but also to companies operating outside the EU, if they have networks or trade data with partners within the EU. Enforcement is expected to start in the spring of 2018.

    The European commission’s website states that:

    The objective of this new set of rules is to give citizens back control over of their personal data, and to simplify the regulatory environment for business.

    Furthermore, as reported by consultancy group itgovernance,

    The Regulation will enforce tough penalties – proposed fines up to 4% of annual global revenue or €20million, whichever is greater

    For a large multinational the fines could get very substantial and significantly impact on share prices.

    The GDPR sets out 8 Data Protection Principles that must be followed. The ICO, UK’s independent Information Commission, has provided clarification of how these principles need to be applied. For example, Principle 1 refers to Processing personal data fairly and lawfully. As described on their website,

    In practice means that you must:

    • have legitimate grounds for collecting and using the personal data;
    • not use the data in ways that have unjustified adverse effects on the individuals concerned;
    • be transparent about how you intend to use the data, and give individuals appropriate privacy notices when collecting their personal data;
    • handle people’s personal data only in ways they would reasonably expect; and
    • make sure you do not do anything unlawful with the data

    Perhaps one of the key new areas is in the use of big data and analytics for customer profiling. This is covered under Principle 6 of the GDPR under the somewhat obtuse description of ‘automated decision making’. ComputerWeekly have produced a number of documents and guides to help businesses to understand how the GDPR will affect them. In one of their latest blogs they explain

    The regulation introduces a number of restrictions on profiling, including the right for an individual not to be subject to a decision which significantly affects the individual and which is based on automated profiling. In many cases, profiling will only be permitted where the explicit consent of the individual has been obtained. 

    The implications for targeted marketing are unclear, but potentially significant, as it makes companies accountable for ensuring that customers

    1. Are made fully aware of exactly how their data will be used
    2. Explicitly agree to the way in which the data will be used
    3. Do not suffer any negative consequences from the use of their data.

    As ComputerWeekly reports

    These restrictions are likely to have a considerable impact on businesses engaging in, for example, big data analytics, as well as more general business activities, such as credit scoring and employee monitoring

    In an article by the International Association of Privacy Professionals , they add that data subjects (customers)

    …may also request to know the purposes of processing, the period of time for which data will be stored, the identity of any recipients of the data, the logic of automatic data processing, and the consequences of any profiling.

    Corporations are now in real danger of drifting into a situation in which they are in breach of the new regulations, face substantial fines and seriously damage customer relations.

    In the final blog of this series I will be looking at how customers are becoming increasingly concerned at the inability of corporations to keep their data safe, and how high publicity data breaches are eroding public confidence.

  • Customer Analytics :  Meeting the Model Me

    Customer Analytics : Meeting the Model Me

    In my last blog I discussed how different generations are challenging marketing departments to meet them on their own ground. For one key demographic, the Millennials, that ground is the mobile and highly social world in which these digital natives live. For another, the more cost conscious middle aged parents with teenage kids, the battleground is through more conventional channels. However it’s not enough to just choose the right channel for marketing a product. The products, product branding, and marketing language itself needs to be appropriate for those customers as well. Different customers have not only different expectations of the products they use, but also different expectations of the way they like to be told about those products.

    The one thing all customers have in common is that they like to be treated as individuals. Individualism is a relatively recent phenomenon in human history, although it could be said to have first really been expressed by Jean-Jacques Rousseau (1712-1778), as Angus Jenkinson identified in his paper ‘Beyond Segmentation’. Rousseau says that truth is subjective, and that traditions and customs must pass the individual’s test ‘can they be authentic for me’. That is a test that consumers increasingly appraise every product with. Can it be authentic for me?

    It may seem an impossible challenge to treat every customer in a way which is appropriate to them alone, but there is another approach which can help product designers and marketing departments have a much better understanding of customers, and that is through the use of persona.

    The concept of archetypes and persona was formalized early in the 20th century by the Swiss psychologist Carl Jung, but it was the Angus Jenkinson who more recently defined the meaning in a marketing context. Jenkinson suggested that marketing needed to move beyond the top down reductionist approach of segmentation and take a more bottom up approach of grouping customers with similar attitudes and behaviors.

    ‘segmentation, as normally understood, represents only the first stage in response to the market (individualism) phenomena. It is the first breakdown of the monolithic market into smaller units. It is possible to go further.’

    There are definitely strong similarities between the concepts of segmentation and grouping, but there is a fundamental, if subtle difference. It is the difference between gathering individuals into groups, as opposed to dividing the group into segments. As Jenkinson says,

    It is much easier to think of developing a relationship with a group (of people) than a segment. How many segments do you personally have a relationship with? Do you want to be part of one? A group connotes…a community of individuals.

    Consumers, as individuals tend to gravitate and have loyalty towards something. To change the corporate perception of customers from being part of a segment to being individuals in a group is a fundamental paradigm shift in building customer relationships, and it requires marketers to develop a much more personal understanding of their customers. Marketers have to understand customer goals and frustrations, their values and behaviors. It is with this new understanding of the importance of the individual that the marketing concept of the ‘persona’ has arrived. Personas are ‘model’ characters created to represent all the members of a group. The term persona as used in this context was actually coined in 1999 by Alan Cooper in his seminal book ‘The Inmates Are Running the Asylum’, in which he says that persona, among other benefits,

    Provide a human “face” so as to create empathy for the persons represented by the demographics.

    Not only do persona models give a detailed account of the emotional needs and values of that group, they often even include a picture of what a typical individual in that group may look like. This is not to say that segmentation is dead. Far from it. Segmentation is still an important tool to help identify the key groups of ideal buyers, but once those groups have been identified then persona need to be created for the segments to give them emotional characteristics and values that they can be identified with. Only by understanding what really motivates customers and providing products that fit in with customer’s lives can marketers grow brand loyalty and trust in a world where the customer is truly king.

    In the fourth in this series of customer analytics blogs, Walking in the Customers Shoes, I will be looking at combining the concept of persona with customer journey mapping to understand how to deliver a better customer experience.

  • Customer Analytics : Gen X and Y and the Millennial Divide

    Customer Analytics : Gen X and Y and the Millennial Divide

    We live in a world where technology is like a digital liquid that’s flowed around every aspect of our lives. There’s no doubt that technology can help to oil the craggy wheels of daily life, and while some find this enabling and liberating, others consider the intrusion to be more insidious. Working out where people stand on this issue is generally just a simple matter of checking their birth date. Many born before 1980 tends to view social and on line everything with suspicion, whereas those consumers born after that date, referred to as Generation Y, or Millennials, are far more comfortable with social media and sharing everything online. In a recent report from Pew research it was shown that the Millennials are much greater users of social media than their parents.

    This is probably because Millennials are the first generation that have grown up entirely with the internet and mobile phones.  They are ‘digital natives’. It’s difficult to know exactly what effects this has on general culture, but one surprising change is that Millennials tend to be far more optimistic that their parents were when they were young. While Generation X and before are more inclined to have a cynical and pessimistic attitude towards the future, a recent report by the Pew Research Centre, Millennials in Adulthood, has found that, despite feeling detached from politics or religion and burdened by debt and recession, the Millennials are inexplicably much more optimistic. According to a recent Gallup poll, eighty percent of millennials, aged 18 to 29, feel positive about the future and say their standard of living is improving.  The reasons for this relentless optimism are unclear but researchers at Pew have pondered that it may be down to more nurturing parenting, or perhaps it’s because millennials always feeling at the centre of their own social network.

    Another characteristic of the millennial generation is that, contrary to predictions that technology would free us all from work, they are now working harder and are more driven to succeed than ever before. In his book ‘Generational Teaching: Motivating the Minority’ Christopher Alan has also found that Millennials are ‘more polite and considerate’, ‘attentive and respectful’ and prefer to work in teams rather than in a hierarchy. Goldman Sachs also says that they are also more health conscious and savvy than earlier generations.   But, as ever, the picture is never that simple, because it seems that the Millennial generation is itself divided in two, as Pew Research has written

    Just 40% of adults ages 18 to 34 consider themselves part of the “Millennial generation,” while another 33% – mostly older Millennials – consider themselves part of the next older cohort, Generation X.

    This all has very great implications on marketing, and how companies should reach out to different generations. Connecting with customers is one of the greatest challenges marketers face, and capturing Millennials is now one of the key battlefields for competing companies. As Leah Swartz of Millennial Marketing says

    ‘When it comes to fashion and shopping, there isn’t a more important demographic for retailers to reach than millennials.’

    Goldman Sachs have even put together an infographic dedicated to marketing to Millennials in which they identify several key things to consider when marketing to the ‘largest generation in US history’. In summary they are

    • Living at home longer
    • Marrying later
    • Sharing, not owning
    • Exercise choice in purchasing
    • More health conscious

    From a non-millennials perspective it may seem that they are so immersed in instant messaging and playing computer games that they are oblivious to the real world, but, on the contrary, millennials are very much aware of the state of the world. It’s just that this revolution is a lot quieter than the ones before, taking place as it does silently from the screens of our phones and laptops. The silence is an illusion. The volume of noise is now measured in packets of data rather than decibels, and it’s loader than ever. If companies don’t engage with different generations of customers on their own ground then they will not be heard at all.

    In my next blog I will look at how Millennials and other demographic groups can be better served by adopting a customer-centric approach to marketing.